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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Early therapeutic effects of adaptive servo-ventilation on cardiac sympathetic nervous function in patients with heart failure evaluated using a combination of {sup 11}C-HED PET and {sup 123}I-MIBG SPECT

Rationale: Adaptive servo-ventilation (ASV), a novel respiratory support therapy for sleep disorders, may improve cardiac function in heart failure (HF). However, the reasons that ASV improves cardiac function have not been fully studied especially in sympathetic nervous function (SNF). The purpose of the present study was to investigate the effects of ASV therapy on cardiac SNF in patients with HF. Methods: We evaluated ASV therapeutic effects before and 6 months after ASV therapy in 9 HF patients [57.3 ± 17.3 years old, left ventricular ejection fraction (LVEF) 36.1 ± 16.7%]. We performed echocardiography, polysomnography, biomarkers, {sup 11}C-hydroxyephedrine (HED) PET as a presynaptic function marker and planar {sup 123}I-metaiodobenzylguanidine (MIBG) to evaluate washout rate. Results: ASV therapy reduced apnea-hypopnea index (AHI) and improved plasma brain natriuretic peptide (BNP) concentration. In {sup 123}I-MIBG imaging, the early heart/mediastinum (H/M) ratio increased after ASV therapy (2.19 ± 0.58 to 2.40 ± 0.67; P = 0.045). Washout rate did not change (23.8 ± 7.3% to 23.8 ± 8.8%; P = 0.122). Global {sup 11}C-HED retention index (RI) improved from 0.068 ± 0.033/s to 0.075 ± 0.034/s (P = 0.029). Conclusions: ASV reduced AHI and improved BNP. ASV might initially improve presynaptic cardiac sympathetic nervous function in HF patients after 6 months of treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Efficient data-driven models for prediction and optimization of geothermal power plant operations

Increasing the capacity of geothermal energy as a renewable resource calls for development and deployment of efficient control and optimization technologies for geothermal power plants. A data-driven prediction and optimization model is presented as a cost-effective and efficient alternative to physics-based approach. The model predicts power output and operational cost by propagating the influence of control and disturbance variables within an artificial neural network (ANN). Numerical experiments with simulated and field data from a real geothermal power plant are first used to demonstrate the prediction performance of the ANN model. The model is then adopted to maximize the net predicted power production by automatically adjusting the working fluid circulation rate. The optimization performance of the model in evaluated using a thermodynamic flowsheet simulation model. The workflow is applied to model and control the effect of ambient temperature on an air-cooled binary cycle power plant, which is complex and costly to perform using a physics-based predictive model. As a result, the performance of the method is demonstrated by applying it to both simulated and field datasets from a binary cycle geothermal power plant.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Improved Li storage performance in SnO 2 nanocrystals by a synergetic doping

Tin dioxide (SnO 2 ) is a widely investigated lithium (Li) storage material because of its easy preparation, two-step storage mechanism and high specific capacity for lithium-ion batteries (LIBs). In this contribution, a phase-pure cobalt-doped SnO 2 (Co/SnO 2 ) and a cobalt and nitrogen co-doped SnO 2 (Co-N/SnO 2 ) nanocrystals are prepared to explore their Li storage behaviors. It is found that the morphology, specific surface area, and electrochemical properties could be largely modulated in the doped and co-doped SnO 2 nanocrystals. Gavalnostatic cycling results indicate that the Co-N/SnO 2 electrode delivers a specific capacity as high as 716 mAh g –1 after 50 cycles, and the same outstanding rate performance can be observed in subsequent cycles due to the ionic/electronic conductivity enhancement by co-doping effect. Further, microstructure observation indicates the existence of intermediate phase of Li 3 N with high ionic conductivity upon cycling, which probably accounts for the improvements of Co-N/SnO 2 electrodes. Furthermore, we find that the method of synergetic doping into SnO 2 with Co and N, with which the electrochemical performances is enhanced remarkably, undoubtedly, will have an important influence on the material itself and community of LIBs as well.

25 ENERGY STORAGE↗
DOE OSTI2024

First application of a liquid argon time projection chamber for the search for intranuclear neutron-antineutron transitions and annihilation in 40 Ar using the MicroBooNE detector

We present a novel methodology to search for intranuclear neutron-antineutron transition (n→n̅) followed by n̅-nucleon annihilation within an 40 Ar nucleus, using the MicroBooNE liquid argon time projection chamber (LArTPC) detector. A discovery of n→n̅ transition or a new best limit on the lifetime of this process would either constitute physics beyond the Standard Model or greatly constrain theories of baryogenesis, respectively. The approach presented in this paper makes use of deep learning methods to select n→n̅ events based on their unique features and differentiate them from cosmogenic backgrounds. The achieved signal and background efficiencies are (70.22 ± 6.04)% and (0.0020 ± 0.0003)%, respectively. A demonstration of a search is performed with a data set corresponding to an exposure of 3.32 ×10 26 neutron-years, and where the background rate is constrained through direct measurement, assuming the presence of a negligible signal. With this approach, no excess of events over the background prediction is observed, setting a demonstrative lower bound on the n→n̅ lifetime in 40 Ar of τ m ≳ 1.1×10 26 years, and on the free n→n̅ transition time of τ n→n̅ ≳ 2.6×10 5 s, each at the 90% confidence level. This analysis represents a first-ever proof-of-principle demonstration of the ability to search for this rare process in LArTPCs with high efficiency and low background.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Younger facial looks are associate with a lower likelihood of several age-related morbidities in the middle-aged to elderly

Abstract Background Looking older for one’s chronological age is associated with a higher mortality rate. Yet it remains unclear how perceived facial age relates to morbidity and the degree to which facial ageing reflects systemic ageing of the human body. Objectives To investigate the association between ΔPA and age-related morbidities of different organ systems, where ΔPA represents the difference between perceived age (PA) and chronological age. Methods We performed a cross-sectional analysis on data from the Rotterdam Study, a population-based cohort study in the Netherlands. High-resolution facial photographs of 2679 men and women aged 51.5–87.8 years of European descent were used to assess PA. PA was estimated and scored in 5-year categories using these photographs by a panel of men and women who were blinded for chronological age and medical history. A linear mixed model was used to generate the mean PAs. The difference between the mean PA and chronological age was calculated (ΔPA), where a higher (positive) ΔPA means that the person looks younger for their age and a lower (negative) ΔPA that the person looks older. ΔPA was tested as a continuous variable for association with ageing-related morbidities including cardiovascular, pulmonary, ophthalmological, neurocognitive, renal, skeletal and auditory morbidities in separate regression analyses, adjusted for age and sex (model 1) and additionally for body mass index, smoking and sun exposure (model 2). Results We observed 5-year higher ΔPA (i.e. looking younger by 5 years for one’s age) to be associated with less osteoporosis [odds ratio (OR) 0.76, 95% confidence interval (CI) 0.62–0.93], less chronic obstructive pulmonary disease (OR 0.85, 95% CI 0.77–0.95), less age-related hearing loss (model 2; B = −0.76, 95% CI −1.35 to −0.17) and fewer cataracts (OR 0.84, 95% CI 0.73–0.97), but with better global cognitive functioning (g-factor; model 2; B = 0.07, 95% CI 0.04–0.10). Conclusions PA is associated with multiple morbidities and better cognitive function, suggesting that systemic ageing and cognitive ageing are, to an extent, externally visible in the human face.

Mekić, Selma↗
DOE OSTI2024

A Novel Spinel High-Entropy Oxide (Cr0.2Mn0.2Co0.2Ni0.2Zn0.2)3O4 as Anode Material for Lithium-Ion Batteries

In this study, we synthesized spinel high-entropy oxide (HEO) (Cr0.2Mn0.2Co0.2Ni0.2Zn0.2)3O4 nanoparticles by a simple solution combustion method. These particles were investigated for their performance as anodes in lithium-ion batteries. The reversible capacity is 132 mAh·g−1 after 100 cycles at a current density of 100 mA·g−1, 107 mAh·g−1 after 1000 cycles at a current density of 1 A g−1, and 96 mAh·g−1 rate capacity at a high current density of 2 A g−1. The outstanding cycle stability under high current densities and remarkable rate performance can be attributed to the stable structure originating from the high entropy of the material.

25 ENERGY STORAGE↗
DOE OSTI2012

The application of Plant Reliability Data Information System (PRINS) to CANDU reactor

As risk-informed applications (RIAs) are actively implanted in the nuclear industry, an issue associated with technical adequacy of Probabilistic Safety Assessment (PSA) arises in its modeling and data sourcing. In Korea, PSA for all Korean NPPs has been completed and KHNP(Korea Hydro and Nuclear Power Plant Company) developed the database called the Plant Reliability Data Information System (PRinS). It has several characteristics that distinguish it from other database system such as NPRDs (INPO,1994), PRIS (IAEA), and SRDF (EdF). This database has the function of systematic data management such as automatic data-gathering, periodic data deposition and updating, statistical analysis including Bayesian method, and trend analysis of failure rate or unavailability. In recent PSA for CANDU reactor, the component failure data of EPRI ALWR URD and Component Reliability Database were preferentially used as generic data set. The error factor for most component failure data was estimated by using the information NUREG/CR-4550 and NUREG/CR-4639. Also, annual trend analysis was performed for the functional losses of components using the statistical analysis and chart module of PRinS. Furthermore, the database has been updated regularly and maintained as a living program to reflect the current status. This paper presents the failure data analysis using PRinS which provides Bayesian analysis on main components in the CANDU reactor. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Efficient Anomaly Detection Driven By Different Machine Learning Architectures And Models

The rapid growth and ubiquitous adoption of the internet and cyber-physical systems (CPS) have fundamentally transformed modern communication, work, and human-system interactions. While networks now form the backbone of critical digital ecosystems, enabling seamless data transmission across diverse, interconnected systems, this increased connectivity also expands the attack surface, making real-time detection of network intrusions and anomalies a pressing challenge. Detecting unusual activities within network infrastructure requires advanced data traffic analysis to differentiate between legitimate and malicious interactions. Traditional approaches to network anomaly detectionâ??such as rule-based and signature-based systemsâ??often depend on predefined patterns to identify known anomalies, limiting their effectiveness against emerging, stealthy, or previously unseen threats. These conventional methods suffer from high false alarm rates and fail to adapt to the ever-evolving nature of network traffic, particularly in large-scale, decentralized environments where data volume, velocity, and variety are constantly increasing. This dissertation presents artificial intelligence (AI)-driven approaches to anomaly detection that leverage graphics processing unit (GPU)-enabled high-performance computing (HPC) platforms for processing massive network traffic data and monitoring the components of cyber-physical systems (CPS) for potentially hazardous conditions. The research advances several key contributions: (1) Designing efficient machine learning techniques for CPS condition monitoring and anomaly detection; (2) enabling federated learning (FL) frameworks that enable distributed detection while preserving data privacy and system resilience; (3) exploring graph-based methodologies combining graph neural networks (GNN) and graph machine learning (ML) approaches for the Internet of Things (IoT) and automotive network security, and (4) performing distributed edge computing optimizations that integrate FL with scalable technologies for reduced communication overhead. Through extensive experiments, these methodologies demonstrate that complex anomaly detection and condition monitoring tasks can be achieved while balancing computational efficiency and detection accuracy through fine-grained network information processing. The frameworks developed in this research establish a robust foundation for network anomaly detection, providing scalable, adaptive, and privacy-preserving solutions for safeguarding CPS and IoT networks in an increasingly interconnected digital landscape. The practical implications of these research findings are significant, as they can inform the development of next-generation network security systems and contribute to the protection of critical infrastructure against sophisticated cyber attacks.

Marfo, William↗
DOE OSTI2024

An Na/TM-site Mg substituted P2-Na 2/3 [Fe 1/3 Mg 1/12 Mn 7/12 ]O 2 cathode with extremely high capacity for sodium-ion batteries

The anionic redox reaction (ARR) has become a hot topic in battery research due to its ability to provide high energy density. Nevertheless, there are still many issues in Na-based layered oxides with the ARR, such as large voltage hysteresis, lattice oxygen loss, irreversible structural changes, and cation migration in the TM layer, resulting in structural collapse and poor electrochemical performance. Herein, a series of Na 2/3 [Fe 1/3 Mg x Mn 2/3–x ]O 2 cathodes are synthesized using a traditional solid-state reaction method. The effectiveness of Mg substitution amounts and site occupancy in regulating the reversibility of the ARR has been explored using various experimental techniques. Surprisingly, the well-designed Na/TM-site Mg substituted P2-Na 2/3 [Fe 1/3 Mg 1/12 Mn 7/12 ]O 2 exhibits an extremely high initial reversible capacity of ~253.21 mA h g –1 , equivalent to ~0.94 e – transfer, which is contributed by both cationic and anionic redox reactions as confirmed by hard X-ray absorption spectroscopy (hXAS) and soft X-ray absorption spectroscopy (sXAS) analyses. In addition, the improved cycling and high-rate performance of the P2-Na 2/3 [Fe 1/3 Mg 1/12 Mn 7/12 ]O 2 are achieved by a well-maintained crystal structure and the highly reversible anionic redox reaction of O 2– /O n– . Finally, these in-depth studies provide crucial knowledge for the development and understanding of cathode materials with a highly reversible ARR for low-cost and high-energy sodium-ion batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Single phase melt processed powellite (Ba,Ca)MoO4 for the immobilization of Mo-rich nuclear waste

Cs is one of the more problematic fission product radionuclides to immobilize due to its high volatility at elevated temperatures, ability to form water soluble compounds, and its mobility in many host materials. The hollandite structure is a promising crystalline host for Cs immobilization and has been traditionally fabricated by solid state sintering methods. This study presents the structure and performance of Ba{sub 1.0}Cs{sub 0.3}A{sub 2.3}Ti{sub 5.7}O{sub 16}; A = Cr, Fe, Al hollandite fabricated by melt processing. Melt processing is considered advantageous given that melters are currently in use for High Level Waste (HLW) vitrification in several countries. This work details the impact of Cr additions that were demonstrated to i) promote the formation of a Cs containing hollandite phase and ii) maintain the stability of the hollandite phase in reducing conditions anticipated for multiphase waste form processing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Modeling Isothermal Reduction of Iron Ore Pellet Using Finite Element Analysis Method: Experiments & Validation

Iron ore pellet reduction experiments were performed with pure hydrogen (H2) and mixtures with carbon monoxide (CO) at different ratios. For direct reduction processes that switch dynamically between reformed natural gas and hydrogen as the reductant, it is important to understand the effects of the transition on the oxide reduction kinetics to optimize the residence time of iron ore pellets in a shaft reactor. Hence, the reduction rates were studied by varying experimental parameters such as the temperature (800, 850 & 900 °C), reactant gas flow rate (100, 150 & 200 cm3/min), pellet size and composition of the reactant gas mixture. The rate of reduction was observed to increase with an increase in temperature and reactant gas flow rate, but it decreased with an increase in pellet size. SEM greyscale analysis was performed to analyze the porosity and phase composition of partially reduced pellets. The porosity of the pellets was observed to increase from 0.3 for unreacted pellet to 0.42 for a completely reduced pellet. Energy-dispersive X-ray spectroscopy (EDAX) analysis was performed to identify the phases observed in the SEM images. The fraction of iron phase was observed to increase from the shell region of the pellet to the core region with an increase in the degree of reduction. A 2D-axisymmetric numerical model was developed on COMSOL Multiphysics, and it was validated using the conversion (X) vs. time curves obtained from each experiment. The model was able to accurately predict the total time needed for the complete conversion of a single iron ore pellet for multiple experiments. Effects of changes in the porosity and tortuosity of the pellet on the model were also studied and the rate of reduction was observed to be sensitive to changes in both porosity and tortuosity. The SEM analysis and the model results show that tortuosity is higher for pellets reduced with H2 than for pellets reduced with H2-CO gas mixtures.

08 HYDROGEN↗
DOE OSTI2016

Impact of axial velocity and transmembrane pressure (TMP) on ARP filter performance

The Savannah River Site (SRS) is currently treating radioactive liquid waste with the Actinide Removal Process (ARP) and the Modular Caustic Side Solvent Extraction Unit (MCU). Recently, the low filter flux through the ARP of approximately 5 gallons per minute has limited the rate at which radioactive liquid waste can be treated. Salt Batch 6 had a lower processing rate and required frequent filter cleaning. Savannah River Remediation (SRR) has a desire to understand the causes of the low filter flux and to increase ARP/MCU throughput. One potential method for increasing filter flux is to adjust the axial velocity and transmembrane pressure (TMP). SRR requested SRNL to conduct bench-scale filter tests to evaluate the effects of axial velocity and transmembrane pressure on crossflow filter flux. The objective of the testing was to determine whether increasing the axial velocity at the ARP could produce a significant increase in filter flux. The authors conducted the tests by preparing slurries containing 6.6 M sodium Salt Batch 6 supernate and 2.5 g MST/L, processing the slurry through a bench-scale crossflow filter unit at varying axial velocity and TMP, and measuring filter flux as a function of time.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

High-temperature electrochemical performance of low-cost La–Ni–Fe based hydrogen storage alloys with different preparation methods

Highlights: • Effects of four different preparation processes were studied at 20/60 °C. • All NS + HT, RS and RS + HT processes can optimize the thermodynamic performance. • The HT process can provoke the precipitation of A{sub 2}B{sub 7} and leads to a poor cycling life. • Al exhibits the most remarkable dissolution for all the alloys, especially at 60 °C. - Abstract: In order to optimize the microstructure and high temperature electrochemical performances of low-cost AB{sub 5}-type Ml(NiMnAl){sub 4.2}Co{sub 0.3}Fe{sub 0.5} hydrogen storage electrode alloys, four different preparation methods including normal solidification (NS), normal solidification and 900 °C heat treatment (NS + HT), rapid solidification (RS), rapid solidification and 900 °C heat treatment (RS + HT) were adopted in this work. All alloys exhibit CaCu{sub 5} type hexagonal structure and there is a small amount of A{sub 2}B{sub 7} phase in NS + HT and RS + HT alloys. It is found the using of HT process can decrease the hydrogen equilibrium plateau pressure, the plateau slope and hysteresis at 40, 60 and 80 °C. The NS + HT and RS + HT alloys also possess better activation, high rate discharge performance, larger discharge capacity, but poor cycling performance due to the existence of A{sub 2}B{sub 7} phase which can accelerate dissolution of Ni, Mn and Fe elements in KOH alkaline electrolyte. The RS process can make alloy exhibit the best cycling performance especially at 60 °C.

36 MATERIALS SCIENCE↗
DOE OSTI2016

MO-AB-BRA-03: Development of Novel Real Time in Vivo EPID Treatment Verification for Brachytherapy

Purpose: High Dose Rate (HDR) brachytherapy treatments are employed worldwide to treat a wide variety of cancers. However, in vivo dose verification remains a challenge with no commercial dosimetry system available to verify the treatment dose delivered to the patient. We propose a novel dosimetry system that couples an independent Monte Carlo (MC) simulation platform and an amorphous silicon Electronic Portal Imaging Device (EPID) to provide real time treatment verification. Methods: MC calculations predict the EPID response to the photon fluence emitted by the HDR source by simulating the patient, the source dwell positions and times, and treatment complexities such as tissue compositions/densities and different applicators. Simulated results are then compared against EPID measurements acquired with ∼0.14s time resolution which allows dose measurements for each dwell position. The EPID has been calibrated using an Ir-192 HDR source and experiments were performed using different phantoms, including tissue equivalent materials (PMMA, lung and bone). A source positioning accuracy of 0.2 mm, without including the afterloader uncertainty, was ensured using a robotic arm moving the source. Results: An EPID can acquire 3D Cartesian source positions and its response varies significantly due to differences in the material composition/density of the irradiated object, allowing detection of changes in patient geometry. The panel time resolution allows dose rate and dwell time measurements. Moreover, predicted EPID images obtained from clinical treatment plans provide anatomical information that can be related to the patient anatomy, mostly bone and air cavities, localizing the source inside of the patient using its anatomy as reference. Conclusion: Results obtained show the feasibility of the proposed dose verification system that is capable to verify all the brachytherapy treatment steps in real time providing data about treatment delivery quality and also applicator/structure motion during or between treatments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A Novel Form of Breast Intraoperative Radiation Therapy With CT-Guided High-Dose-Rate Brachytherapy: Results of a Prospective Phase 1 Clinical Trial

Purpose: Existing intraoperative radiation therapy (IORT) techniques are criticized for the lack of image guided treatment planning and energy deposition with, at times, poor resultant dosimetry and low radiation dose. We pioneered a novel method of IORT that incorporates customized, computed tomography (CT)-based treatment planning and high-dose-rate (HDR) brachytherapy to overcome these drawbacks: CT-HDR-IORT. Methods and Materials: A phase 1 study was conducted to demonstrate the feasibility and safety of CT-HDR-IORT. Eligibility criteria included age ≥50 years, invasive or in situ breast cancer, tumor size <3 cm, and N0 disease. Patients were eligible before or within 30 days of breast-conserving surgery (BCS). BCS was performed, and a multilumen balloon catheter was placed. CT images were obtained, a customized HDR brachytherapy plan was created, and a dose of 12.5 Gy was delivered to 1-cm depth from the balloon surface. The catheter was removed, and the skin was closed. The primary endpoints were feasibility and acute toxicity. Feasibility was defined as IORT treatment interval (time from CT acquisition until IORT completion) ≤90 minutes. The secondary endpoints included dosimetry, cosmetic outcome, quality of life, and late toxicity. Results: Twenty-eight patients were enrolled. The 6-month follow-up assessments were completed by 93% of enrollees. The median IORT treatment interval was 67.2 minutes (range, 50-108 minutes). The treatment met feasibility criteria in 26 women (93%). The dosimetric goals were met in 22 patients (79%). There were no Radiation Therapy Oncology Group grade 3+ toxicities; 6 patients (21%) experienced grade 2 events. Most patients (93%) had good/excellent cosmetic outcomes at the last follow-up visit. Conclusions: CT-HDR-IORT is feasible and safe. This promising approach for a conformal, image-based, higher-dose breast IORT is being evaluated in a phase 2 trial.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

A COMPARISON OF FLARE FORECASTING METHODS. I. RESULTS FROM THE “ALL-CLEAR” WORKSHOP

Solar flares produce radiation that can have an almost immediate effect on the near-Earth environment, making it crucial to forecast flares in order to mitigate their negative effects. The number of published approaches to flare forecasting using photospheric magnetic field observations has proliferated, with varying claims about how well each works. Because of the different analysis techniques and data sets used, it is essentially impossible to compare the results from the literature. This problem is exacerbated by the low event rates of large solar flares. The challenges of forecasting rare events have long been recognized in the meteorology community, but have yet to be fully acknowledged by the space weather community. During the interagency workshop on “all clear” forecasts held in Boulder, CO in 2009, the performance of a number of existing algorithms was compared on common data sets, specifically line-of-sight magnetic field and continuum intensity images from the Michelson Doppler Imager, with consistent definitions of what constitutes an event. We demonstrate the importance of making such systematic comparisons, and of using standard verification statistics to determine what constitutes a good prediction scheme. When a comparison was made in this fashion, no one method clearly outperformed all others, which may in part be due to the strong correlations among the parameters used by different methods to characterize an active region. For M-class flares and above, the set of methods tends toward a weakly positive skill score (as measured with several distinct metrics), with no participating method proving substantially better than climatological forecasts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Robust Period Estimation Using Mutual Information for Multiband Light Curves in the Synoptic Survey Era

The Large Synoptic Survey Telescope (LSST) will produce an unprecedented amount of light curves using six optical bands. Robust and efficient methods that can aggregate data from multidimensional sparsely sampled time-series are needed. Here, we present a new method for light curve period estimation based on quadratic mutual information (QMI). The presented method does not assume a particular model for the light curve nor its underlying probability density and it is robust to non-Gaussian noise and outliers. By combining the QMI from several bands the true period can be estimated even when no single-band QMI yields the period. Period recovery performance as a function of average magnitude and sample size is measured using 30,000 synthetic multiband light curves of RR Lyrae and Cepheid variables generated by the LSST Operations and Catalog simulators. The results show that aggregating information from several bands is highly beneficial in LSST sparsely sampled time-series, obtaining an absolute increase in period recovery rate up to 50%. We also show that the QMI is more robust to noise and light curve length (sample size) than the multiband generalizations of the Lomb–Scargle and AoV periodograms, recovering the true period in 10%–30% more cases than its competitors. A python package with efficient Cython implementations of the QMI and other methods is provided.

79 ASTRONOMY AND ASTROPHYSICS↗